Abstract
Artificial Immune Recognition System (AIRS) has been shown to be an effective classifier for several machine learning problems. In this study, AIRS is investigated as a classifier for musical genres from differing cultures. Musical data of two cultures were used - Traditional Malay Music (TMM) and Latin Music (LM). The performance of AIRS for the classification of these genres was compared with performances using several commonly used classifiers. The best classification accuracy for TMM was obtained using AIRS and was comparable, almost similar, to the performance obtained with the popular classifiers. However, the performance of AIRS for LM genre classification was shown to be not promising.
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Doraisamy, S., Golzari, S. (2010). Automatic Musical Genre Classification and Artificial Immune Recognition System. In: Raś, Z.W., Wieczorkowska, A.A. (eds) Advances in Music Information Retrieval. Studies in Computational Intelligence, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11674-2_17
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DOI: https://doi.org/10.1007/978-3-642-11674-2_17
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